Optimal design for inference on the threshold of a biomarker.
| Autor: | Baldi Antognini A; Department of Statistical Sciences, University of Bologna, Bologna, Italy., Frieri R; Department of Statistical Sciences, University of Bologna, Bologna, Italy., Rosenberger WF; Department of Statistics, George Mason University, Faifax, VA, USA., Zagoraiou M; Department of Statistical Sciences, University of Bologna, Bologna, Italy. |
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| Jazyk: | angličtina |
| Zdroj: | Statistical methods in medical research [Stat Methods Med Res] 2024 Feb; Vol. 33 (2), pp. 321-343. Date of Electronic Publication: 2024 Jan 31. |
| DOI: | 10.1177/09622802231225964 |
| Abstrakt: | Enrichment designs with a continuous biomarker require the estimation of a threshold to determine the subpopulation benefitting from the treatment. This article provides the optimal allocation for inference in a two-stage enrichment design for treatment comparisons when a continuous biomarker is suspected to affect patient response. Several design criteria, associated with different trial objectives, are optimized under balanced or Neyman allocation and under equality of the first two empirical biomarker's moments. Moreover, we propose a new covariate-adaptive randomization procedure that converges to the optimum with the fastest available rate. Theoretical and simulation results show that this strategy improves the efficiency of a two-stage enrichment clinical trial, especially with smaller sample sizes and under heterogeneous responses. Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. |
| Databáze: | MEDLINE |
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